Regulatory Compliance, Risk Management, And AI

AI’s ability to adapt and learn from new data enables it to produce outputs such as predictions, recommendations, and decisions that influence its environment. During a recent webinar highlighted in an article by Navex, experts Jan Stappers and Caro Robson explored the continually changing intersection of regulatory compliance, risk management, and AI.

They highlighted AI’s capability to draw conclusions from data sets it apart from traditional computing, which relies on predetermined codes. While this gives AI significant power, it also introduces complexity and unpredictability, which brings specific risks, especially related to third-party and supply-chain vulnerabilities.

Developing AI models involves collecting and processing large datasets, which is resource-intensive and has significant human and environmental costs. The production processes often lack transparency, raising concerns about environmental impact and labor practices. Once developed, AI models are integrated into software products, potentially introducing biases and data privacy issues. This necessitates greater transparency in data usage and transfer across supply chains.

AI also plays a crucial role in Environmental, Social, and Governance (ESG) reporting, but reliance on products from opaque supply chains can complicate the accuracy of these reports. Managing AI-related risks involves understanding the AI systems and their data, implementing robust security measures, and adopting standard risk management practices. Having a clear AI policy and ensuring supply chain transparency are essential steps.

The European Union’s upcoming AI Act aims to provide a regulatory framework that categorizes AI systems by risk levels, balancing safety and innovation. This act, along with other regulations like GDPR and cybersecurity directives, aims to protect consumers and businesses while promoting ethical standards.

AI offers immense benefits but also presents unique risks, particularly in supply chains and data management. By understanding these risks and implementing comprehensive compliance strategies, organizations can effectively utilize AI’s potential while mitigating potential challenges.